Data can conventionally be acquired from various data detectors, such as, for example, digital cameras, medical imaging systems, and nuclear detectors. The acquired data is typically processed to create a desired output, such as a two-dimensional or three-dimensional image. Although data acquisition in a simple imaging system does not usually suffer from any bottlenecks, typical data acquisition systems can be unreliable in high count rate applications. The unreliability of these systems is due to the relatively large dead-time for their imaging electronics, their difficulty in discriminating detector output pulses, their loss of useful data signals, their relatively low sampling rate, their relatively low pulse pileup recovery rate, and their relatively high susceptibility to noise.
As such, many efforts have been made to enhance signal quality and spatial resolution by reducing noise, pileup, baseline drift, and ballistic deficit. However, prior techniques were forced to compromise between their defects such that, for example, by improving the count rate, the signal quality was lowered. Moreover, signals acquired from photomultiplier tubes have noise and exponential decay time, which introduces imprecision in extraction of the pure signal. As such, a new system and method is needed to accurately distinguish pulse shapes in high count rate systems without the limitations of conventional data acquisition systems.